Traditional ultrasound B-Scan images show the envelope of received echoes as a grey scale image. The echoes are produced from specular reflections and scattering sites where changes in acoustic impedance occur. A long- standing area of interest concerns the frequency dependence of backscattered ultrasound from within different tissues. Some advanced backscatter analyses estimate the frequency dependence and angular dependence of backscattered waves. However, most statistical averaging techniques require some region of interest over which to calculate the expected value of scattering parameters. Unfortunately, the unfavorable statistics of ultrasound echoes can limit the spatial resolution or accuracy of these estimators. Specific changes in pathology can cause changes in the underlying size, structure, and composition of tissue, and so the goal of somehow capturing these changes remains. We hypothesize that a new matched filter approach using matched Hermite functions can classify and visualize major scattering classes at high resolution. This enables clinicians to distinguish subtle cellular and parenchymal changes that would otherwise appear similar, thereby adding new and relevant information to diagnostic ultrasound. The recently derived H-scan is a fresh approach where the received echoes can be linked to three major classes of echoes from tissues. Echoes are linked to the mathematics of Gaussian Weighted Hermite Polynomials so that the overall identification task can be simplified. The resulting images are denoted as H-scans, where ?H? represents Hermite or hue, since the identification by hue is distinct from the traditional B-scan. The framework was given an initial test in biological tissues ? liver and placenta ? where changes in tissue H-scan images are plausibly linked to changes in the concentration of small scatterers. However, in order to establish H-Scan as a viable diagnostic technique, two issues must be proven. First, the H-scan must be shown to give consistent results within tissues over a range of depths and despite attenuation. Second, the H-scan must be shown to be sensitive to cellular and sub-cellular changes in tissue scatterers, relevant to a clinically significant condition. This project will address both these issues. The depth and attenuation dependence will be studied and corrected in a series of phantom and tissue experiments. The sensitivity and accuracy will be tested in a liver steatosis model in rats. The results should establish the key performance issues for H-scan, and thereby characterize its ability to advance diagnostic ultrasound imaging for assessing pathology in humans.